Venkatesh Ramaiyan

We consider an ad hoc wireless network where all nodes have data to send to a single destination node called the sink. We consider a linear placement of the wireless nodes with the sink at one end. We assume that the wireless nodes transfer data to the sink using single hop direct transmission and that the nodes are scheduled one at a time by a central scheduler (possibly the sink). In this setup, we assume that the wireless nodes are power limited and our network objective (notion of fairness) is to maximize the minimum throughput of a node subject to the individual node power constraints. In this work, we consider network designs that permit different node transmission time, node transmission power and node placements, and study cross-layer strategies that seek to maximize the minimum node throughput. Using simulations, we characterize the performance of the different strategies and comment on their applicability for various network scenarios. © 2013 IEEE.

We consider a collocated WLAN with Nac 802.11ac users using dynamic 20/40 MHz channel access and Nl 802.11a/n legacy users operating in the secondary 20 MHz channel. Under ideal channel conditions, we seek to characterise the saturation throughput performance of the 802.11ac users and the legacy users. We propose an analytical model based on a decoupling approximation for saturation throughput analysis. Dynamic bandwidth channel access leads to correlation in the channel access of 802.11ac and legacy users and hence, we consider a DTMC to model the transmission opportunities in the primary and the secondary channel. Using simulations, we show that the proposed model accurately captures both high level performance measures such as long term average throughput and low level performance measures such as collision probability very well. Finally, we characterise the effect of Nac, Nl and packet size on the network performance.

We study a problem of sequential frame detection in an asynchronous framework, where a single frame of length N slots is transmitted uniformly in a large interval of known size A slots. In this setup, we seek to characterize the scaling needed of N and the channel (input) parameters for asynchronous optimal frame synchronization. We note that the framework permits a natural trade-off between N and \alpha , where \alpha is the synchronization threshold of the channel (usually parameterized by the channel input). We present a general framework that permits this trade-off and then characterize the scaling needed of both N and \alpha as a function of the asynchronism period A. Finally, we apply our results to the AWGN channel as an illustration.

SimRank is a widely studied link-based similarity measure that is known for its simple, yet powerful philosophy that two nodes are similar if they are referenced by similar nodes. While this philosophy has been the basis of several improvements, there is another useful, albeit less frequently discussed interpretation for SimRank known as the Random Surfer-Pair Model. In this work, we show that other well known measures related to SimRank can also be reinterpreted using Random Surfer-Pair Models, and establish a mathematically sound, general and unifying framework for several link-based similarity measures. This also serves to provide new insights into their functioning and allows for using these measures in a Monte Carlo framework, which provides several computational benefits. As an illustration of its utility in designing measures, we develop a new measure based on two existing measures under this framework, and empirically demonstrate its efficacy.

We consider a slotted wireless network in an infrastructure setup with a base station (or an access point) and N users. The wireless channel gain between the base station and the users is assumed to be i.i.d. over users and slots, and the base station seeks to schedule the user with the highest channel gain in every slot (opportunistic scheduling). We assume that contention for opportunistic scheduling is resolved using a series of minislots and with feedback from the base station. In this setup, we formulate the contention resolution problem for opportunistic scheduling as identifying a random threshold (channel gain) that separates the best channel from the other samples. The average delay minimization for contention resolution is then related to entropy (of the random threshold) minimization, which is a concave minimization problem. We illustrate our formulation by studying a popular contention resolution strategy called the opportunistic splitting algorithm (OSA, [9]). OSA is a greedy algorithm that maximizes the probability of success in every minislot. We study the delay and entropy optimality of OSA for i.i.d. wireless channel. Finally, we discuss the applicability of the entropy minimization framework to identify optimal contention resolution strategies for general network scenarios. © 2014 IEEE.

We seek to study Wi-Fi coverage and performance in typical Indian homes, and appreciate infrastructure deployment strategies for whole home coverage with throughput guarantees. We prefer experiments in real homes for performance evaluation, and measured coverage and throughput performance in homes of different sizes and types, in 2.4 GHz and 5 GHz band, and with 1x1 and 2x2 client devices of different make and price range. The measurements allowed us to characterize coverage as a function of the size of the home and the band of operation, and characterize throughput as a function of signal strength, bandwidth of operation and radio capability of the devices. We also validated the observations with limited experiments in a static channel. Finally, based on our measurements, we make recommendations on network architecture, AP placement and radio configuration for whole home coverage with 100 Mbps guaranteed throughput.

We consider a problem of asynchronous communication over a discrete memoryless channel (DMC). A transmitter seeks to communicate B bits of information to a receiver at a random time V. For a general distribution of V , we propose an asymptotically error-free variable length coding scheme that adapts the codeword length and distribution based on the arrival probabilities in a slot. For a simple class of L-step arrival distributions, we characterize the capacity of the DMC, and also show that the variable length coding scheme achieves higher rates and lower cost of communication in comparison with the fixed length coding scheme studied in prior works. Using numerical work, we illustrate our results for a binary symmetric channel in a number of interesting scenarios.

We study a problem of covert communication over binary symmetric channels (BSC) in an asynchronous setup. Here, Alice seeks to communicate to Bob over a BSC while trying to be covert with respect to Willie, who observes any communication through possibly a different BSC. When Alice communicates, she transmits a message (using a codeword of length n) at a random time uniformly distributed in a window of size Aw slots. We assume that Bob has side information about the time of transmission leading to a reduced uncertainty of Ab slots for Bob, where A_b< A_w. In this setup, we seek to characterize the limits of covert communication as a function of the timing advantage. When Aw is increasing exponentially in n, we characterize the covert capacity as a function of Aw and Ab. When Aw is increasing sub-exponentially in n, we characterize lower and upper bounds on achievable covert bits and show that positive covert rates are not feasible irrespective of timing advantage. Using numerical work, we illustrate our results for different network scenarios, and also highlight a tradeoff between timing advantage and channel advantage (between Bob and Willie).

In this paper, we study completely uncoupled learning algorithms for general utility maximization. We illustrate the algorithm with a wireless network application viz distributed user association. Our main contribution is expansion of achievable rate region by allowing time sharing of resources, which the previous works based on completely uncoupled strategies have ignored. First, we present a distributed user association algorithm based on a state space expansion that can achieve any desired throughput vector in the rate region of the wireless network. Then, for concave utility functions, we present a stochastic gradient algorithm with fewer synchronization requirements than known references.

We study a problem of scheduling real-time traffic with hard delay constraints in an unreliable wireless channel. We consider the uplink channel of an infrastructure network with a base station and a fixed number of wireless users. Packets are generated at a constant rate and they need to be delivered to the base station within a fixed number of slots. In a fading wireless channel, we are interested in the fraction of packets that can be successfully delivered within the hard delay bound. Using a notion of rate region, we provide a characterization of the achievable packet delivery rates for the wireless network. We consider a general network model that permits multiple access as a contention mechanism to schedule a user. The multiple access strategy improves the achievable packet delivery rates in comparison with earlier works such as. We discuss rate optimal and utility maximizing strategies for the network using the rate region framework. Using simulations, we evaluate the performance of the multiple access strategy and discuss its advantages. © 2012 IEEE.